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HoneyHive is an observability and evaluation platform designed specifically for production AI agents. Built by a team focused on AI reliability, it solves the problem of debugging, monitoring, and improving agent behavior at scale. Core capabilities include distributed tracing with OpenTelemetry, online and offline evaluation, monitoring and alerts, experiment management, and annotation queues for human feedback. It supports over 100 LLMs and agent frameworks, making it framework-agnostic. The platform is used by teams ranging from AI startups to Fortune 500 enterprises, such as Commonwealth Bank of Australia, to ensure safe and responsible deployment of AI agents. HoneyHive unifies observability and evaluation into a continuous improvement loop, enabling teams to ship quality agents with confidence. It offers both SaaS and self-hosted deployment options with strong data isolation and security features.
4.5/5
High, consistent, and on-brand
Clean and minimal
Unify observability and evaluation for production AI agents.
Integrates with any model, framework, or agent runtime supporting OpenTelemetry, plus 100+ LLMs and agent frameworks.
Freemium with paid tiers
Features with the highest value for users are highlighted here.
OpenTelemetry-native distributed tracing
Online evaluation with LLM-as-a-judge
Session replays and graph timeline view
Customizable alerts and drift detection
Offline experiments with regression detection
Human review queues with custom rubrics
CI/CD integration for automated testing
Virtual data planes for data isolation
AI Engineers
ML Teams
Product Managers
DevOps / SRE
Enterprise Teams
Startups
Quality Assurance
Coding Agents
Data Scientists
Compliance Officers
Free
Pro
Weekly intelligence on AI strategy, operations, and market shifts. No noise. No narrative. Direct to your inbox.
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